Wireless communication is ubiquitous and deployments are growing rapidly. In 2008 the International Telecommunication Union estimated the number of mobile telephones at 4.1 billion with a worldwide population of approximately 6.8 billion people (ITU Corporate Annual Report, http://www.itu.int/dms_pub/itu-s/opb/conf/S-CONF-AREP-2008-E06-PDF-E.pdf). Portio Research estimates the number of mobile telephones will grow to 5.8 billion by 2013, fueled by Asia-Pacific particularly, which by 2013 will account for 43.9 percent of subscribers, followed by Europe (25.0 percent), Africa and Middle East (12.2 percent), Latin America (11.2 percent) and North America (7.6 percent) (“Mobile Factbook 2009” http://www.portiodirect.com/productDetail.aspx?pid=49$55$51$431). By 2014, global mobile Internet users expected to send and receive 1.6 Exabytes of mobile data each month, which is more than the 1.3 Exabytes transferred during the whole of 2008, according to ABI Research (http://www.abiresearch.com/press/1466-In+2014+Monthly+Mobile+Data+Traffic+Will+Exceed+2008+Total).
Cellular phones are evolving into hand-held computers with voice, data and video multimedia applications and accordingly, there is the associated increasing demand for more bandwidth. IDC estimates the annual shipment of Bluetooth-enabled devices as 1.2 billion devices and growing with 20% CAGR (http://www.idc.com/getdoc.jsp?sessionId=&containerId=219098&sessionId=UDMGOJ2XGTN JMCQJAFICFGAKBEAUMIWD). In-Stat estimates the annual shipment of WLAN-enabled devices is 380 million and growing 24% CAGR (“Global Wi-Fi Chipset Forecast and Analysis: 2007 to 2013” http://www.instat.com/abstract.asp?id=167&SKU=IN0904005WS). Additionally, the cost of deploying a wireless system is decreasing by half compounded every five years (The Economist, Apr. 10, 2008).
By contrast wireless spectrum is a scarce and limited resource allocated in small segments for many different communication uses (see for example www.ntia.doc.gov/osmhome/allochrt.pdf). The recent auction of spectrum in the US provides a good indication of spectrum scarcity and resulting value. In 2008, the US Federal Communications Commission (FCC) auctioned a relatively tiny 62 MHz segment of spectrum across the United States for a total of US$19.6B (http://wireless.fcc.gov/auctions/default.htm?job=auction_summary&id=73) to a collection of telecommunications service providers including Verizon and AT&T. This spectrum was made available as a result of the digital television (DTV) transition away from analog TV (http://en.wikipedia.org/wiki/United_States—2008_wireless_spectrum_auction). To satisfy the increasing demands for performance and throughput, wireless physical layer designs are becoming increasingly complex. It has been nearly thirty years since the first commercial wireless network using frequency division multiple access, so-called 1G technology was developed. Next came time division multiple access (TDMA) in 2G Global System for Mobile Communications (GSM) systems in the 1990s followed by code division multiple access (CDMA) in 3.xG systems in the early 2000s. 4G networks of Long Term Evolution (LTE) and WiMax are currently in the planning and deployment stages and the next generation wireless local area network (LAN) 802.11n systems are pushing throughput towards 100 Mbps with Multiple-Input-Multiple-Output (MIMO) and orthogonal frequency division multiple access (OFDMA) approaches. Such modern wireless communication systems employ sophisticated RF technologies that include frequency hopping, complex modulation and packet-based transmission formats. These new data-centric wireless systems are complex to deploy, operate, maintain and monitor.
Wireless communications is becoming increasingly subjected to radio interference. As the density of wireless devices increases so does the density of wireless base stations. To satisfy a city of millions of cellular users, each with increased cellular usage, requires a progressively denser mesh of cellular base stations, and these increasingly interfere with each other. Simultaneously corporations are increasingly deploying or expanding wireless networks. Wireless 802.11 LAN occupies the same spectrum as Bluetooth, cordless phones and microwave ovens and “must accept any interference” (en.wikipedia.org/wiki/ISM_band). In addition to these sources of unintentional interference there is the issue of RF devices transmitting with malicious intent. Radio jamming for instance refers to the transmission of RF signals that disrupt communication networks by decreasing the signal-to-interference ratio.
The rapid growth of deployments, scarcity of spectrum, complexity of solutions, congestion and interference are increasingly compounded problems for those deploying, managing, maintaining and monitoring wireless services. Wireless spectrum is a shared resource. Worldwide national governments not only license the use of the spectrum but must also police that spectrum. Policing ensures that those who are not authorized are not transmitting and those who have spent billions of dollars for licensing have unencumbered access. Specifically, government agencies monitor the wireless spectrum within their countries to determine the occupancy within specific segments of the spectrum, to enforce allocation and to police issues pertaining to interference. Currently, these agencies typically deploy laboratory or hand-held spectrum analyzers that are expensive and not designed for remote deployment. Consequently they are required to maintain and deploy expensive personnel and equipment to monitor wireless activity within their network, which can as a result be intermittent in nature.
Wireless communications and networks are deployed by telecommunications service providers, governments, corporations and the home user. Service providers are challenged by the compounding problems of increased number and density of users, increased user usage, and demands for increased bandwidth. The deployment, operation and maintenance of next generation wireless services are as a result increasing the demands for test, monitoring and “visibility” of the wireless physical layer. Similar to government agencies, service providers currently must deal with deployment issues by similarly maintaining and deploying expensive personnel and equipment to at best accomplish intermittent and often inadequate monitoring.
Corporate and government information technology (IT) groups face similar if not worse problems in the deployment, operation and maintenance of wireless networking infrastructure. The suite of IEEE 802.11 wireless products operate in unlicensed frequency bands. As a result, wireless LANs face interference from the deployment of not only other wireless LANs but also other wireless devices such as Bluetooth devices, cordless phones and even microwave ovens. So the IT departments are faced with not only the increasing demand for density and bandwidth, but also interference from a broad range of sources which may be transitory in nature and agile in frequency.
In addition to ensuring wireless connectivity, preventing wireless connectivity has also become an issue. A growing segment of large corporate and government departments for example require the enforcement of a no-wireless policy. A no-wireless policy is intended to prevent for example the inadvertent or malicious listening of sensitive, proprietary, confidential or secret information within meeting rooms via a cell phone or an eavesdropping device. Such policy enforcement is challenged by the breadth and complexity of wireless devices, which are evolving rapidly in terms of functionality, complexity and performance.
Applications for spectrum monitoring also extend to other environments, for example the battlefield. Equipping military personnel with the means to monitor and analyze their RF environment for communication activity, signal jammers and other threats is becoming a necessity in today's world of ubiquitous wireless devices, improvised explosive devices with remote triggers, etc.
Accordingly there exists an increasing demand for real-time monitoring of the wireless environment across extended geographical areas. It is not sufficient for example to simply monitor at a discrete location within a hospital, it should be all over the hospital, nor is it sufficient to monitor at specific locations within an urban environment as increasingly the wireless infrastructure moves from large cell structures to picocells and femtocells. The applications of such real-time distributed analysis included interference detection, no-wireless or selective-wireless policy enforcement, spectrum management, signals intelligence (SIGINT), communications intelligence (COMINT), electronic intelligence (ELINT) and signal/interference analysis. In respect of policy enforcement this may be over a discrete area such as a shop, a floor of an office building for example or a large area such as an enterprise environment, a mall, a downtown business district, an airport, hospital or other geographically distributed environment.
For illustrative purposes of a selective wireless policy implementation a network administrator may allow signal transmissions with specified maximum amplitude characteristics in different frequency bands. At the same time transmissions in some frequency bands are prohibited and the specifications of allowed frequency bands may also vary from one geographic area of the enterprise to another. The requirement is to detect any violation in this policy and inform the network administrator of the breach as soon as it occurs. It would be apparent that many such selective wireless policies might exist.
Today wireless signal analysis is typically performed only in laboratory environments or with very limited, customized field applications. This arises from consideration of the availability of test equipment, which is generally large, expensive microwave test equipment, from companies such as Agilent, Tektronix, Anritsu, Ando, etc, allowing measurements and analysis over a wide frequency spectrum, for example 0 MHz-6000 MHz (6 GHz) rather than specific application test equipment addressing a particular niche market with limited functionality and limited frequency range, e.g. the portable tester a cable engineer comes to a residence with that only needs to address a 83 MHz range for IEEE 802.11b WiFi applications. Wireless, RF and microwave applications range within the United States are covered by the FCC regulations up to 300 GHz (see http://www.ntia.doc.gov/osmhome/allochrt.html for allocations) but for the limitation of discussions within this document applications to an upper limit of 6 GHz are considered for explanation purposes only.
Accordingly it would be beneficial to provide low cost signal analyzers with broadband performance allowing them to be deployed across a geographic area or within a predetermined region. It would be further beneficial if the signal analyzers communicated with a centralized remote server allowing an overall picture of the wireless activity within an area to be ascertained, tracked and monitored. Early work in addressing this requirement, see for example S. R. Morton et al in U.S. Pat. No. 5,103,402 entitled “Method and Apparatus for Identifying, Saving, and Analyzing Continuous Frequency Domain Data in a Spectrum Analyzer”, considered how to handle data accumulated at a rate faster than real-time display means and hence approached the issue by continuously storing the scanned spectra into a memory for subsequent retrieval and display as a surface plot rather than the normal amplitude versus frequency plot. However, such methods merely addressed the ability of conventional spectrum analyzers, upon which the methods were based, to accumulate date faster than a user could review.
More recent work by Cognio Inc., now part of Cisco Systems Inc., has considered signal analysis for determining whether to jam an unauthorized transmission occurring within a predetermined region, see for example N. R. Diener et al in U.S. Pat. No. 7,142,108 entitled “System and Method for Monitoring and Enforcing a Restricted Wireless Zone” (hereinafter referred to as Diener '108). Diener '108 teaches that at each location within the predetermined region a spectrum monitoring section analyses all activity within a narrow predetermined band, e.g. 2.400-2.483 GHz ISM, 5.725-5.825 GHz Upper U-NII (U-NII-3) band for, based upon applying a Fast-Fourier Transform (FFT) to received pulsed signals with multiple FFT intervals to determine a power versus frequency plot. This data is then sent, using a different frequency range and transmission standard, to a central server for every cycle of the FFT process along with additional information derived from a co-hosted traffic monitoring station that operates using International standard protocols, such as IEEE 802.11, to generate probe requests and receive responses allowing legitimate traffic to be identified or transmitting nodes operating according to the International standard to be located. However, Diener '108 requires that a large amount of information is continuously transmitted (wirelessly) from the monitoring nodes to the server for analysis, irrespective of whether the information transmitted is about legitimate sources or otherwise.
A similar system is presented by N. R. Diener et al in U.S. Pat. No. 7,184,777 entitled “Server and Multiple Sensor System for Monitoring Activity within a Shared Radio Frequency Band” (hereinafter referred to as Diener '777) which omits the jamming elements within the remote nodes of Diener '108. Diener '777 addresses the identification of non-standard transmitters operating in the same frequency band as a wireless LAN (WLAN) within an enterprise. As with Diener '108 Diener '777 considers these signal analyzers to be targeted to a specific telecommunications standard and narrow frequency range, such as monitoring and analyzing an IEEE 802.11 (WiFi) WLAN, e.g. operating at the 5.725-5.825 GHz Upper U-NII (U-NII-3) band, and continuously streams spectrum measurement data to the central server via wireless links according to another wireless standard which may or may not be retrieved for subsequent review. Non-standard transmitters according to Diener '777 are determined by the co-hosted traffic monitoring station that operates using same standard protocol as the WLAN and it is these spectrum measurements that Diener '777 teaches as being viewed.
Each of Diener '108 and Diener '777 utilize a real-time spectrum analysis engine (SAGE) as described by G. L. Sugar et al in U.S. Pat. No. 7,224,752 entitled “System and Method for Real-Time Spectrum Analysis in a Communication Device” which is a hardware accelerator implemented in standard CMOS electronics to determine information about pulses occurring within the predetermined frequency range of the SAGE. As such the SAGE generates continuously data such as start time, duration, power, center frequency and bandwidth of signals detected within the local region of the antenna feeding the SAGE. As noted supra in respect of Diener '108 and Diener '777 the SAGE has a bandwidth of approximately 100 MHz as the applications are specific network applications such as the monitoring of a WLAN on a single floor within an office building. The centralized management taught by Diener '108 and Diener '777 receives the continuous stream of power/frequency data and presents this data to the central manager for determination of action.
However, today multiple networks are operating simultaneously within the environment of a user who may for example be working at their laptop with a WiFi wireless router (e.g. 5.775 GHz U-NII-3 based IEEE 802.11) interfaced to the Internet whilst talking using a Bluetooth (unlicensed 2.4 GHz) headset to a Voice-over-IP (VOIP) with their Research in Motion™ Blackberry operating at 1.9 GHz on GSM. Accordingly it would be beneficial to cost-effectively monitor geographical areas for signal activity within multiple frequency bands managed by a network and communicate notifications of policy breaches to the administrator whilst also providing direct local signaling which may be used to adjust an operational aspect of the signal analyzer or wireless environment. Accordingly each signal analyzer according to embodiments of the invention only transmits to the central management systems in the event of a policy breach, the policy breach may be specific to that signal analyzer or associated with a predetermined portion of the network. Should communications to the central server systems be interrupted the local policy management allows devolved processing, decision-making and local caching of data.
A policy breach can lead to subsequent action by the central server to initiate signal analysis operations. For example, relevant data is streamed from the signal analyzer to the server and further processed for message content. A system of priority may be assigned whereby this data stream is processed with greater urgency than data streams from other analyzers.
It is, therefore, desirable to provide low cost, broadband signal analysis in a distributed environment wherein determination of policy breaches are locally determined and communicated to the central server and network administrators. Beneficially such local determination reduces communication overheads across the network and permits local action to be taken in the event of communications failure. The benefits of an automated system of notification are many, for example, the administrator does not have to manually, continuously monitor spectral data to determine if a breach has occurred.